Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models | Paper Citation Record

Observation 2974fbd3-2dc1-499d-99c4-b28632754de1 · outbound

This paper cites Battaglini, L.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Battaglini, L

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This paper cites De Roux, B.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models De Roux, B

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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This paper cites Rahman, V.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Rahman, V

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This paper cites De Caigny, K.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models De Caigny, K

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Verboven, N

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Malgieri, F

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This paper cites Asgeirsson, The nature and value of vagueness in the law, Bloomsbury Publishing, 2020.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Asgeirsson, The nature and value of vagueness in the law, Bloomsbury Publishing, 2020

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This paper cites Hildebrandt, The adaptive nature of text-driven law, Journal of Cross-disciplinary Research in Computational Law 1 (2021).

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Hildebrandt, The adaptive nature of text-driven law, Journal of Cross-disciplinary Research in Computational Law 1 (2021)

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This paper cites Weerts, R.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Weerts, R

Reference 10

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This paper cites Dari-Mattiacci, B.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Dari-Mattiacci, B

Reference 11

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This paper cites Siena, J.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Siena, J

Reference 12

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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This paper cites Hardt, E.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Hardt, E

Reference 15

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Shanmugam, F

Reference 16

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Goldsteen, G

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Goldsteen, O

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This paper cites Rudin, Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead, Nature machine intelligence 1 (2019) 206–215.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Rudin, Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead, Nature machine intelligence 1 (2019) 206–215

Reference 19

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Fresz, E

Reference 20

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This paper cites Wachter, B.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Wachter, B

Reference 21

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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This paper cites Agarwal, Trade-o ffs between fairness and privacy in machine learning, in: IJCAI 2021 Workshop on AI for Social Good, 2021.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Agarwal, Trade-o ffs between fairness and privacy in machine learning, in: IJCAI 2021 Workshop on AI for Social Good, 2021

Reference 23

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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This paper cites Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Toward the Tradeoffs between Privacy, Fairness and Utility in Federated Learning

Reference 25

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This paper cites SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models SoK: Taming the Triangle -- On the Interplays between Fairness, Interpretability and Privacy in Machine Learning

Reference 26

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This paper cites On the Trade-Off between Actionable Explanations and the Right to be Forgotten.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models On the Trade-Off between Actionable Explanations and the Right to be Forgotten

Reference 27

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This paper cites Xhemajli, The role of ethics and morality in law: Similarities and di fferences, Ohio NUL Rev.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Xhemajli, The role of ethics and morality in law: Similarities and di fferences, Ohio NUL Rev

Reference 28

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This paper cites Gardner, 35 ethics and law, The Routledge Companion to Ethics (2010).

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Gardner, 35 ethics and law, The Routledge Companion to Ethics (2010)

Reference 29

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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This paper cites Lewkowicz, R.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Lewkowicz, R

Reference 31

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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This paper cites Blackman, Ethical machines: Your concise guide to totally unbiased, transparent, and respectful AI, Harvard Business Press, 2022.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Blackman, Ethical machines: Your concise guide to totally unbiased, transparent, and respectful AI, Harvard Business Press, 2022

Reference 33

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This paper cites Compatibility of Fairness Metrics with EU Non-Discrimination Laws: Demographic Parity & Conditional Demographic Disparity.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Compatibility of Fairness Metrics with EU Non-Discrimination Laws: Demographic Parity & Conditional Demographic Disparity

Reference 34

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This paper cites Kerrigan, Artificial intelligence: Law and regulation, Edward Elgar Publishing, 2022.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Kerrigan, Artificial intelligence: Law and regulation, Edward Elgar Publishing, 2022

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This paper cites Hadjiemmanuil, A heavily regulated industry, eucrim (2015).

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Hadjiemmanuil, A heavily regulated industry, eucrim (2015)

Reference 36

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This paper cites Shen, Ai regulation in health care: How washington state can conquer the new territory of ai regulation, Seattle J.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Shen, Ai regulation in health care: How washington state can conquer the new territory of ai regulation, Seattle J

Reference 37

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Rethinking Legal Compliance Automation: Opportunities with Large Language Models

Reference 38

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This paper cites Sleimi, M.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Sleimi, M

Reference 39

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This paper cites Akhigbe, D.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Akhigbe, D

Reference 40

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Legal Requirements Analysis

Reference 41

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Faßbender, Domain-and Quality-aware Requirements Engineering for Law-compliant Systems, Ph.D

Reference 42

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Hoess, N

Reference 43

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Gjorgjevikj, K

Reference 44

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Zowghi, M

Reference 45

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Ahmad, M

Reference 47

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This paper cites Mart ´ınez-Fern´andez, J.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Mart ´ınez-Fern´andez, J

Reference 48

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Classification, Challenges, and Automated Approaches to Handle Non-Functional Requirements in ML-Enabled Systems: A Systematic Literature Review

Reference 49

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Boella, L

Reference 50

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models doi: 10.1109/IEEESTD.1990.101064

Reference 51

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Van Vliet, H

Reference 52

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Belani, M

Reference 53

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This paper cites Hildebrandt, A.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Hildebrandt, A

Reference 54

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Ghanavati, D

Reference 56

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Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

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This paper cites Requirements Elicitation and Modelling of Artificial Intelligence Systems: An Empirical Study.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Requirements Elicitation and Modelling of Artificial Intelligence Systems: An Empirical Study

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This paper cites Ahmad, M.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Ahmad, M

Reference 59

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Observation 9f60a31a-3b1c-4b49-8291-c2db1edfed9b · outbound

This paper cites Ahmad, C.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Ahmad, C

Reference 60

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Observation 130f94e4-733f-4054-af1f-2a0fd4801a7c · outbound

This paper cites AI for All: Operationalising Diversity and Inclusion Requirements for AI Systems.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models AI for All: Operationalising Diversity and Inclusion Requirements for AI Systems

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-16T11:00:08.771326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e2b7faf-916d-4b4b-868b-86fb76fef1da · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:10.140108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2e3a2bf2-677f-4f90-a9be-0a9ec22e70e4 · outbound

This paper cites Balasubramaniam, M.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Balasubramaniam, M

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:10.127700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 93d2d061-d1a4-4501-aee2-074e7b429fc5 · outbound

This paper cites Damirchi, A.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Damirchi, A

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:10.114942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2f9f81b6-d3a1-43c8-890a-fd7c1b337bb3 · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:10.103559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c3c685d8-81b0-4cd5-8e95-a8646481f7b7 · outbound

This paper cites Sadovski, I.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Sadovski, I

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:10.092045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac5f925d-ee46-4871-a4ea-33d2751e5b4e · outbound

This paper cites Agarwal, Trade-o ffs between fairness and interpretability in machine learning, in: IJCAI 2021 Workshop on AI for Social Good, 2021, pp.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Agarwal, Trade-o ffs between fairness and interpretability in machine learning, in: IJCAI 2021 Workshop on AI for Social Good, 2021, pp

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:10.079860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0142cdfe-1ebb-4b76-9592-3396bcebd4d3 · outbound

This paper cites Jabbari, H.-C.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Jabbari, H.-C

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:10.067828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1eba08a0-ca41-4e8d-9276-f643b5dbf7c8 · outbound

This paper cites Learning Optimal Fair Classification Trees: Trade-offs Between Interpretability, Fairness, and Accuracy.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Learning Optimal Fair Classification Trees: Trade-offs Between Interpretability, Fairness, and Accuracy

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-16T11:00:08.806517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 281c7318-83d0-4674-844a-b61abd8eb707 · outbound

This paper cites Investigating Trade-offs in Utility, Fairness and Differential Privacy in Neural Networks.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Investigating Trade-offs in Utility, Fairness and Differential Privacy in Neural Networks

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-16T11:00:08.812317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70070dbb-97e6-4c84-9b31-0e31a96ebc12 · outbound

This paper cites Gittens, B.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Gittens, B

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:10.055586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c0aaa2a8-8db1-4108-b5ea-d97de60b4504 · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 72

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:10.043000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ff07d8d2-26c7-4e49-befd-eaa0e5573a40 · outbound

This paper cites Finck, A.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Finck, A

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-16T11:00:08.824264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bf4fc30-e3a2-4418-9d3d-c5f28c904820 · outbound

This paper cites Pessach, E.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Pessach, E

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:10.030050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4dcdd804-bf05-492e-a8ca-93caadfa787c · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:10.016115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation df7eb385-10ed-4d7e-ada9-07c2c397bc87 · outbound

This paper cites Bueno Mom ˇcilovi´c, D.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Bueno Mom ˇcilovi´c, D

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:10.000305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 64bf05f1-d149-4e2b-ab00-730300cf9969 · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:09.985733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4da67431-6a22-49f0-a6c9-afd3cbfba544 · outbound

This paper cites right to explanation.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models right to explanation

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.972243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d3248348-529d-47f2-ace9-a9ece41d430f · outbound

This paper cites meaningful information.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models meaningful information

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.959564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 18abaac5-8b03-47d1-826d-a4ace21678d2 · outbound

This paper cites Malgieri, G.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Malgieri, G

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.942883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0bf3d323-21fc-4850-9615-b5b79f738566 · outbound

This paper cites right to explanation.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models right to explanation

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.927250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7b2c2c0b-a4cb-4caf-89b0-34ba8b0730f2 · outbound

This paper cites Wachter, B.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Wachter, B

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.912728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8e6583b8-70e1-4322-996e-e7ae9fe5755f · outbound

This paper cites Custers, New digital rights: Imagining additional fundamental rights for the digital era, Computer Law & Security Review 44 (2022) 105636.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Custers, New digital rights: Imagining additional fundamental rights for the digital era, Computer Law & Security Review 44 (2022) 105636

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.898841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2bde59b8-1c3f-40ca-8eaa-b8c9a56d2f54 · outbound

This paper cites Tridimas, Wreaking the wrongs: Balancing rights and the public interest the eu way, Colum.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Tridimas, Wreaking the wrongs: Balancing rights and the public interest the eu way, Colum

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.885369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9beb662e-b2f2-4f70-bf05-a19e1ccc5a1b · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 85

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:09.870872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation efec545d-3e63-4f1f-963a-8ec681a5a528 · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:09.855616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57c4a435-65f3-4ae6-b155-ca3182bacf86 · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 87

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:09.842680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f2b5823c-cfcd-47b7-aca2-579d277f75bd · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:09.830174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f7f97a3d-26b0-4df1-ab6b-1c2da4ca2b86 · outbound

This paper cites Parente, The ai act and its impacts on the european financial sector, The EUROFI Magazine (2024).

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Parente, The ai act and its impacts on the european financial sector, The EUROFI Magazine (2024)

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.818376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0c983e43-4e50-46d6-a870-af34a0c23c47 · outbound

This paper cites Xenidis, L.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Xenidis, L

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.806737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2c33cff4-9cd6-4cfe-bfea-7cf53235a9c9 · outbound

This paper cites URL: https://fra.europa.eu/ en/publication/2018/handbook-european-non-discrimination-law-2018-edition , accessed: date-of-access.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models URL: https://fra.europa.eu/ en/publication/2018/handbook-european-non-discrimination-law-2018-edition , accessed: date-of-access

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.794321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 183d8755-98fd-4f72-ac71-4616e3a01d2d · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 92

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:09.782675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4882e8ab-360b-49ba-96d4-87874f1526ac · outbound

This paper cites Muir, The horizontal e ffects of charter rights given expression to in eu legislation, from mangold to bauer, Review of European Administrative Law 12 (2019) 185–215.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Muir, The horizontal e ffects of charter rights given expression to in eu legislation, from mangold to bauer, Review of European Administrative Law 12 (2019) 185–215

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.772183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 878f13dc-c96a-4bd8-914f-b7da981ced8d · outbound

This paper cites Bertrand, W.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Bertrand, W

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.760058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 416ff5c6-6a5c-49d0-9fcd-3acae1006cee · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:09.744981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d82aa1c7-df62-4ee0-a40b-f98f4524579b · outbound

This paper cites Article 5.1(c).

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Article 5.1(c)

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.731911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b1f53c39-6372-4198-aa88-51286098b90e · outbound

This paper cites Binns, M.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Binns, M

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.719153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eea48b49-c59c-489f-8f1f-921c7c855507 · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 98

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:09.707847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 43f56307-7623-49ba-a655-b075dd2a9cd1 · outbound

This paper cites an unresolved cited work.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Unresolved cited work

Reference 99

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:00:09.693089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a49dc3e5-17e5-4b61-aae0-d6c7ceff4667 · outbound

This paper cites Veale, R.

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models Veale, R

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:00:09.664826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers